Optimal prediction method for CO2 solubility in saline aquifers by DONG Lifei, DONG Wenzhuo, ZHANG Qi, ZHONG Pinzhi, WANG Miao, YU Bo, WEI Haiyu, YANG Chao

“…The predicted values of the grey Markov model were more consistent with the measured data, and the prediction performance of the model was better, so as to provide a new method for predicting the solubility of CO2 in underground salt water.…”
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A Graph Representation Learning-Based Method for Event Prediction by Xi Zeng, Guangchun Luo, Ke Qin, Pengyi Zheng

“…However, events typically encompass a myriad of elements and intricate relationships, necessitating an enhancement in the precision of event prediction. However, the existing methods suffer from poor data quality, insufficient feature information, limited generalization capability of the models, and difficulties in evaluating prediction errors. …”
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A Method of Productivity Prediction for Multi-Fractured Horizontal Well by YANG Fan, GAO Yanwu, SHAO Guanghui, LIU Jieli, XU Rui, ZHOU Jufeng

“…On this basis, the productivity prediction model of horizontal wells is established by using the method of multiple linear regression. …”
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PREDICTION METHOD FOR ACUTE TRAUMATIC PANCREATITIS IN SHOCK-INDUCING POLYTRAUMA by M. F. Cherkasov, O. L. Degtyarev, A. B. Lageza, K. A. Demin

“…Implementation of the scoring evaluation method to identify the risk of pathology onset based on combinations of risk factors considerably increased informative value of predictions and improved the efficiency of individually tailored preventive measures corresponding to the risk of pancreatopathy in shock-inducing polytrauma cases.The authors declare no conflict of interest.The authors confirm that they respect the rights of the people participated in the study, including obtaining informed consent when it is necessary, and the rules of treatment of animals when they are used in the study. …”
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Quantitative method for network security situation based on attack prediction by Hao HU, Run-guo YE, Hong-qi ZHANG, Ying-jie YANG, Yu-ling LIU

“…To predict the attack behaviors accurately and comprehensively as well as to quantify the threat of attack,a quantitative method for network security situation based on attack prediction was proposed.By fusing the situation factors of attacker,defender and network environment,the capability of attacker and the exploitability rate of vulnerability were evaluated utilizing the real-time detected attack events,and the expected time-cost for attack-defense were further calculated.Then an attack prediction algorithm based on the dynamic Bayesian attack graph was designed to infer the follow-up attack actions.At last,the attack threat was quantified as the security risk situation from two levels of the hosts and the overall network.Experimental analysis indicates that the proposed method is suitable for the real adversarial network environment,and is able to predict the occurrence time of attack accurately and quantify the attack threat reasonably.…”
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Quantitative method for network security situation based on attack prediction by Hao HU, Run-guo YE, Hong-qi ZHANG, Ying-jie YANG, Yu-ling LIU

“…To predict the attack behaviors accurately and comprehensively as well as to quantify the threat of attack,a quantitative method for network security situation based on attack prediction was proposed.By fusing the situation factors of attacker,defender and network environment,the capability of attacker and the exploitability rate of vulnerability were evaluated utilizing the real-time detected attack events,and the expected time-cost for attack-defense were further calculated.Then an attack prediction algorithm based on the dynamic Bayesian attack graph was designed to infer the follow-up attack actions.At last,the attack threat was quantified as the security risk situation from two levels of the hosts and the overall network.Experimental analysis indicates that the proposed method is suitable for the real adversarial network environment,and is able to predict the occurrence time of attack accurately and quantify the attack threat reasonably.…”
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A Hybrid GARCH and Deep Learning Method for Volatility Prediction by Hailabe T. Araya, Jane Aduda, Tesfahun Berhane

“…Volatility prediction plays a vital role in financial data. The time series movements of stock prices are commonly characterized as highly nonlinear and volatile. …”
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Student Dropout Prediction Using Random Forest and XGBoost Method by Lalu Ganda Rady Putra, Didik Dwi Prasetya, Mayadi Mayadi

“…Objective: This study aims to evaluate the effectiveness of the Random Forest and XGBoost algorithms in predicting student attrition based on demographic, socioeconomic, and academic performance factors. …”
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Evaluation of predictive maintenance efficiency with the comparison of machine learning models in machining production process in brake industry by Can Aydın, Burak Evrentuğ

“…Methods This study aims to predict machine faults using data analysis methods and enhance the accuracy performance of these predictions for an industrial company that produces braking components. …”
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Constructing a Predictive Model to Evaluate the Risk of CHD Based on New Metabolic Indicators by Wang W, Du Z, Xie P

“…Wenqiang Wang,1 Zonghan Du,2 Peng Xie3 1Department of Nursing, Beijing Anzhen Nanchong Hospital of Capital Medical University & Nanchong Central Hospital, Nanchong, Sichuan, 637000, People’s Republic of China; 2Department of Gastroenterology, Beijing Anzhen Nanchong Hospital of Capital Medical University & Nanchong Central Hospital, Nanchong, Sichuan, 637000, People’s Republic of China; 3Department of Cardiovascular Medicine, Beijing Anzhen Nanchong Hospital of Capital Medical University & Nanchong Central Hospital, Nanchong, Sichuan, 637000, People’s Republic of ChinaCorrespondence: Peng Xie, Department of Cardiovascular Medicine, Beijing Anzhen Nanchong Hospital of Capital Medical University & Nanchong Central Hospital, Nanchong, Sichuan, 637000, People’s Republic of China, Email billxiewang@163.comObjective: Constructing a predictive model to evaluate the risk of coronary heart disease (CHD) for early identification of patients with CHD risk based on new metabolic indicators.Methods: A retrospective analysis was conducted based on NHANES databases. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…This study presents a comparative analysis of hyper-parameter optimization methods used in developing predictive models for patients at risk of heart failure readmission and mortality. …”
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Using Impact Evaluation Tools to Unpack the Black Box and Learn What Works by Laura R Peck

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Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

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Evaluating the relative predictive validity of measures of self-referential processing for depressive symptom severity by Ethel Siew Ee Tan, Hong Ming Tan, Kah Vui Fong, Sheryl Yu Xuan Tey, Nikita Rane, Chong Wei Ho, Zhao Yuan Tan, Rachel Jing Min Ong, Chloe Teo, Jerall Yu, Maxine Lee, An Rae Teo, Sin Kee Ong, Xin Ying Lim, Jin Lin Kee, Jussi Keppo, Geoffrey Chern-Yee Tan

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Utility of laboratory markers in evaluating for acute compartment syndrome in the emergency department by Gregory S. Weingart, Phillip Jordan, Kei‐Lwun Yee, Lauren Green

“…Further research and prospective evaluation of serum markers are needed.…”
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Evaluating the weight-adjusted waist index as a predictive tool for sarcopenia and mortality risk by Qingzheng Shen, Tianjing Zhou, Xiaodong Chen, Hafiz Muhammad Umar, Xinxin Yang, Xian Shen

“…WWI is linked to reduced muscle mass and strength; however, its efficacy for assessing sarcopenia and predicting adverse outcomes has yet to be validated. …”
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Experimental evaluation of an advanced predictive control technique for variable-speed wind turbine systems by Farah Echiheb, Btissam Majout, Ismail EL Kafazi, Badre Bossoufi, Abdelhamid Rabhi, Nicu Bizon, Anton Zhilenkov, Saleh Mobayen

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Model Predictive Control Strategies Performance Evaluation over a Pipeline Transportation System by Jorge Cardenas-Cabrera, Luis Diaz-Charris, Andrés Torres-Carvajal, Narciso Castro-Charris, Elena Romero-Fandiño, José David Ruiz Ariza, Javier Jiménez-Cabas

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H∞ filtering of uncertain predictive models: Gain computation using LMI and performance evaluation by Eli G. Pale Ramon, Oscar G. Ibarra-Manzano, José A. Andrade-Lucio, Yuriy S. Shmaliy

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A Predicting Method of the Strong Cooling Process during Winter with Numerical Model Prediction and its Operational Application by Bomin CHEN, Kun ZHOU, Fei XIN, jun MA, Limei JIN

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